{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from os.path import join\n",
    "import matplotlib.pyplot as plt\n",
    "from glob import glob\n",
    "from keras.models import load_model\n",
    "from matplotlib.colors import LogNorm\n",
    "from scipy.ndimage import gaussian_filter, maximum_filter, minimum_filter\n",
    "from deepsky.gan import unnormalize_multivariate_data\n",
    "from skimage.morphology import disk\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_path = \"/glade/work/dgagne/spatial_storm_results_20171220/\"\n",
    "#data_path = \"/Users/dgagne/data/spatial_storm_results_20171220/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_000.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_001.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_002.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_003.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_004.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_005.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_006.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_007.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_008.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_009.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_010.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_011.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_012.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_013.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_014.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_015.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_016.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_017.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_018.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_019.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_020.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_021.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_022.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_023.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_024.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_025.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_026.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_027.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_028.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_auc_029.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_000.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_001.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_002.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_003.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_004.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_005.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_006.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_007.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_008.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_009.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_010.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_011.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_012.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_013.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_014.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_015.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_016.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_017.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_018.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_019.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_020.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_021.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_022.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_023.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_024.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_025.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_026.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_027.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_028.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_conv_net_bss_029.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_000.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_001.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_002.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_003.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_004.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_005.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_006.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_007.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_008.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_009.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_010.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_011.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_012.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_013.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_014.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_015.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_016.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_017.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_018.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_019.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_020.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_021.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_022.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_023.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_024.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_025.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_026.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_027.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_028.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_auc_029.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_000.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_001.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_002.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_003.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_004.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_005.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_006.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_007.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_008.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_009.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_010.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_011.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_012.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_013.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_014.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_015.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_016.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_017.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_018.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_019.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_020.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_021.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_022.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_023.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_024.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_025.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_026.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_027.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_028.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_mean_bss_029.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_000.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_001.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_002.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_003.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_004.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_005.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_006.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_007.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_008.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_009.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_010.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_011.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_012.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_013.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_014.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_015.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_016.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_017.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_018.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_019.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_020.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_021.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_022.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_023.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_024.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_025.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_026.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_027.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_028.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_auc_029.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_000.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_001.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_002.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_003.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_004.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_005.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_006.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_007.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_008.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_009.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_010.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_011.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_012.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_013.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_014.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_015.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_016.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_017.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_018.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_019.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_020.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_021.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_022.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_023.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_024.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_025.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_026.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_027.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_028.csv\n",
      "/glade/work/dgagne/spatial_storm_results_20171220/var_importance_logistic_pca_bss_029.csv\n"
     ]
    }
   ],
   "source": [
    "scores = [\"auc\", \"bss\"]\n",
    "models = [\"conv_net\", \"logistic_mean\", \"logistic_pca\"]\n",
    "imp_scores = {}\n",
    "for model in models:\n",
    "    imp_scores[model] = {}\n",
    "    for score in scores:\n",
    "        score_files = sorted(glob(data_path + \"var_importance_{0}_{1}_*.csv\".format(model, score)))\n",
    "        imp_score_list = []\n",
    "        for score_file in score_files:\n",
    "            print(score_file)\n",
    "            imp_data = pd.read_csv(score_file, index_col=\"Index\")\n",
    "            imp_score_list.append(((imp_data.iloc[0,0] - imp_data.loc[1:])).mean(axis=0))\n",
    "        imp_scores[model][score] = pd.concat(imp_score_list, axis=1).T\n",
    "        imp_scores[model][score].columns = imp_scores[model][score].columns.str.rstrip(\"_prev\"\n",
    "                                                                    ).str.replace(\"_\", \" \"\n",
    "                                                                    ).str.replace(\"-component of\", \"\"\n",
    "                                                                    ).str.replace(\"dew point temperature\", \"dewpoint\"\n",
    "                                                                    ).str.capitalize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(3, 2, figsize=(12, 12))\n",
    "plt.subplots_adjust(wspace=0.6)\n",
    "model_titles = [\"Conv. Net\", \"Logistic Mean\", \"Logistic PCA\"]\n",
    "for m, model in enumerate(models):\n",
    "    for s, score in enumerate(scores):\n",
    "        rankings = imp_scores[model][score].mean(axis=0).sort_values().index\n",
    "        axes[m,s ].boxplot(imp_scores[model][score].loc[:, rankings].values, vert=False, \n",
    "                         boxprops={\"color\":\"k\"}, whiskerprops={\"color\":\"k\"}, \n",
    "                         medianprops={\"color\":\"k\"}, flierprops={\"marker\":\".\", \"markersize\":3},whis=[2.5, 97.5])\n",
    "        axes[m, s].set_yticklabels(imp_scores[model][score].loc[:, rankings].columns.str.replace(\" mb\", \" hPa\"))\n",
    "        axes[m, s].set_title(model_titles[m] + \" \" + score.upper())\n",
    "        axes[m, s].grid()\n",
    "        #axes[m, s].set_xscale(\"log\")\n",
    "        if m == len(model_titles) - 1:\n",
    "            axes[m, s].set_xlabel(\"Decrease in \" + score.upper(), fontsize=12)\n",
    "plt.savefig(\"var_imp_box.pdf\", dpi=300, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_cols = imp_scores[model][score].columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "log_pca_coefs = np.zeros((30, 75))\n",
    "for i in range(30):\n",
    "    with open(\"/Users/dgagne/data/spatial_storm_results_20171220/\" + \"hail_logistic_pca_sample_{0:03d}.pkl\".format(i), \"rb\") as pca_pkl:\n",
    "        log_pca_model = pickle.load(pca_pkl)\n",
    "    log_pca_coefs[i] = log_pca_model.model.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "log_gan_coefs = np.zeros((30, 64))\n",
    "for i in range(30):\n",
    "    with open(\"/Users/dgagne/data/spatial_storm_results_20171220/\" + \"logistic_gan_{0:d}_logistic.pkl\".format(i), \"rb\") as gan_pkl:\n",
    "        log_gan_model = pickle.load(gan_pkl)\n",
    "    log_gan_coefs[i] = log_gan_model.coef_.ravel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "  <matplotlib.lines.Line2D at 0x1c2ff02d68>,\n",
       "  <matplotlib.lines.Line2D at 0x1c2ff176d8>,\n",
       "  <matplotlib.lines.Line2D at 0x1c2ff17b00>,\n",
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       " 'means': []}"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(np.abs(log_gan_coefs.T))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.abs(log_pca_coefs).min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.YTick at 0x1c2e8edf60>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8ed7f0>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8b9828>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8c9518>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8c99b0>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8c9e80>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8bf390>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8bf860>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8bfd30>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8bd240>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8bd710>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8bdbe0>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8bf470>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8bd860>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e8bdf60>],\n",
       " <a list of 15 Text yticklabel objects>)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6, 10))\n",
    "plt.pcolormesh(np.abs(log_pca_coefs).T, norm=LogNorm(0.0001, 1))\n",
    "plt.yticks(np.arange(0, 75, 5), input_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.YTick at 0x1c2e2d6518>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e2cce10>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e2c7cc0>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e289da0>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e2942b0>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e294780>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e294c88>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e29b1d0>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e29b6d8>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e29bbe0>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e29bcc0>,\n",
       "  <matplotlib.axis.YTick at 0x1c2e294a90>,\n",
       "  <matplotlib.axis.YTick at 0x1c2c4d02e8>,\n",
       "  <matplotlib.axis.YTick at 0x1c2c4d0710>,\n",
       "  <matplotlib.axis.YTick at 0x1c2c4d0c18>],\n",
       " <a list of 15 Text yticklabel objects>)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(np.arange(15), np.abs(log_pca_coefs).mean(axis=0).reshape(15, 5).mean(axis=1))\n",
    "plt.yticks(np.arange(15), input_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "mean_imp_matrix = pd.DataFrame(index=imp_scores[\"conv_net\"][\"bss\"].columns, columns=models, dtype=float)\n",
    "mean_imp_rank_matrix = pd.DataFrame(index=imp_scores[\"conv_net\"][\"bss\"].columns, columns=models, dtype=int)\n",
    "for model in models:\n",
    "    mean_imp_matrix.loc[:, model] = imp_scores[model][\"bss\"].values.mean(axis=0)\n",
    "    rank = np.argsort(imp_scores[model][\"bss\"].values.mean(axis=0))\n",
    "    for r in range(rank.size):\n",
    "        mean_imp_rank_matrix.loc[mean_imp_rank_matrix.index[rank[r]], model] = rank.size - r\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0.68831654,   1.13451656,   1.44212821,   1.55460714,\n",
       "         2.2877488 ,   2.57388041,   3.05342006,   4.78460331,\n",
       "         5.16755414,   7.18191937,   8.33550156,  13.72857337,\n",
       "        14.8664198 ,  19.72752819,  25.62117955])"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_imp_matrix[\"conv_net\"].values[np.argsort(mean_imp_matrix[\"conv_net\"].values)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>conv_net</th>\n",
       "      <th>logistic_mean</th>\n",
       "      <th>logistic_gan</th>\n",
       "      <th>logistic_pca</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>geopotential height 500 mb</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>geopotential height 700 mb</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>geopotential height 850 mb</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>temperature 500 mb</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>temperature 700 mb</th>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>temperature 850 mb</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dew point 500 mb</th>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dew point 700 mb</th>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dew point 850 mb</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u wind 500 mb</th>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u wind 700 mb</th>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u wind 850 mb</th>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>v wind 500 mb</th>\n",
       "      <td>15</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>v wind 700 mb</th>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>v wind 850 mb</th>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           conv_net logistic_mean logistic_gan logistic_pca\n",
       "geopotential height 500 mb        1             1           14           15\n",
       "geopotential height 700 mb        3             4           15            1\n",
       "geopotential height 850 mb        2             2           13           12\n",
       "temperature 500 mb                8             7            3           14\n",
       "temperature 700 mb                6             3           12           13\n",
       "temperature 850 mb                4             5            7           11\n",
       "dew point 500 mb                 10            15            6           10\n",
       "dew point 700 mb                 12             9           10            9\n",
       "dew point 850 mb                  5             6            2            8\n",
       "u wind 500 mb                    14            13           11            7\n",
       "u wind 700 mb                    11            10            5            6\n",
       "u wind 850 mb                     7             8            1            5\n",
       "v wind 500 mb                    15            12            8            4\n",
       "v wind 700 mb                    13            14            9            3\n",
       "v wind 850 mb                     9            11            4            2"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_imp_rank_matrix"
   ]
  }
 ],
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